Predicting the Isotropic Volumetric Compression Response of Hydrating Cemented Paste Backfill (CPB)
Bibliographic record
Abstract
Abstract Deep and high-stress mining results in stress transfers onto the previously placed backfill, and mines have recorded several MPa induced backfill stress. Understanding the backfill-rock mass interaction is therefore critical. Previous work considered tabular ore bodies undergoing primarily one-dimensional compression and showed how the backfill reaction curves could be estimated from oedometer laboratory test results. This work considers massive orebodies and develops a similar approach based on isotropic compression curves. Isotropic compression tests exceeding 6 MPa are carried out on samples with 3.0–11.1% binder content, tested at 1-day cure time to 28-day cure time. The compression curve is characterized in three stages: initial elastic compression up to a yield point, followed by a transition stage to the start of a final stage with a linear post-yield compression line in \({\epsilon }_{v}-\text{l}\text{o}\text{g}\left({p}^{\text{'}}\right)\) space. Because these isotropic compression tests are rare (the reported results are the first for Cemented Paste Backfill), attempts are made to relate the isotropic compression test parameters to parameters from the more commonly used Unconfined Compression Strength (UCS) tests. Unifying equations as functions of binder content and cure time are found to determine the initial yield stress and the peak strength from UCS tests. These are then related to the corresponding parameters in isotropic compression. Finally, the slope of the post-yield compression line is found as a function of UCS, thereby enabling complete reconstruction of the isotropic compression response based on parameters from carefully controlled UCS tests, as functions of binder content and cure time. Although the calibrated parameters are specific to the studied mine’s materials, the framework is general and applicable to other mines’ CPBs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".